The present invention relates to a system for optically measuring pitting and general corrosion in surfaces of metals. More particularly the invention relates to an optical system for measuring more than one type of corrosion in metals such as aluminum.
At the present time, corrosion-related experiments are performed on metal coupons in order to obtain information about the use of the metal in actual applications. Metal coupons are the xe2x80x9cwork-horsexe2x80x9d of the corrosion monitoring industry, and it is a very cheap method for what is now a multi-million dollar industry. The coupons are examined for corrosion after exposure to predetermined and measured conditions using several methods.
One method is based on weight-loss of the coupons. The coupon weight before and after the corrosion experiment provides a difference that is related to corrosion activity. Another method is to measure changes in electrical resistance, but this requires sophisticated calibrations that are difficult to interpret. Visual inspection of the coupon is also performed to determine the area of the coupon that is affected by corrosion. Both these corrosion measurements are inaccurate and subjective.
Other methods have been proposed for observing materials. U.S. Pat. No. 5,332,900, Witzke et al. uses an on-line monitoring system in which the metal is irradiated and observed with an optical system. U.S. Pat. No. 5,623,341, Hunt, uses nonlinear second order surface spectroscopy to monitor the condition of a surface for corrosion and other changes. U.S. Pat. No. 5,208,162, Osborne et al., employs a piezoelectric crystal system. U.S. Pat. No. 5,155,555 uses a coupon that is inserted into a fluid and removed for observation using reflected light. None of these systems provide for a simple and effective method for measurement of corrosion on metal such as metal coupons.
It would be of great advantage in the art if a more accurate method of measuring corrosion activity could be provided.
It would be another great advance in the art if the method of measuring corrosion activity would reduce or eliminate subjective measurements, and quantify actual corrosion activity.
Another advantage would be if calculations of the corrosion activity could be done autonomously.
Other advantages will appear hereinafter.
It has now been discovered that the above and other objects of the present invention may be accomplished in the following manner. Specifically, the present invention provides a process for autonomously determining the amount of corrosion that has occurred to a metal coupon, such as an aluminum coupon, for a given environment and time. The invention comprises a combination of a digital camera focused on a metal coupon, providing digital images of the coupon by the digital camera, and analyzing the image using an algorithm.
The Coupons that are used are cropped within the field of view of a macro lens digital camera. The digitization consists of intensity values of from 0 to 255, with 0 representing the color black and 255 representing the color white. Inbetween 0 and 255 are varying shades of gray. An image of a non-corroded coupon, or calibration coupon, is taken to get the minimum and maximum intensity values. The intensity values that trend toward 0 or black are an indication of corrosion by pitting. Intensity values that trend toward 255 or white are an indication of oxidization.
Using the corrosion image from the digital camera, a threshold for the image is calculated and the values that are greater than or less than that of the threshold are summed, to give an estimated area of corrosion for the coupon. Varying the threshold and observing the resulting image with the original corrosion image gives a better estimate of the corrosion for the coupon being inspected. Black pixels indicate a pitting action, so changing the threshold for black pixels will isolate the pits and cumulative pit area can be estimated by summing the pixels that are less than a given threshold.
The pixels are arranged using a standard clustering algorithm such as the k-means algorithm. Then, the type of corrosion, pitting or general, is determined using a classification algorithm such as one using neural networks.